Recent genome-wide association studies (GWAS) of psoriasis have identified 41 psoriasis susceptibility loci, and we are currently applying multiple genetic and genomic assets to the molecular genetic dissection of psoriasis, which provide a uniquely powerful platform for identification of causal variants in PsC and PsA. Finding the functional basis of disease-associated genetic variation is a major goal in the analysis of disease associations in psoriasis and all complex genetic disorders, because it provides a molecular link between genotype and phenotype. To date, however, convincing demonstration of disease associated variant-specific function is uncommon in psoriasis as well as in other complex genetic disorders. In many instances, this has been due to incomplete and/or inaccurate determination of the functional variants. The statistical expertise that we will bring t bear on our unique datasets will allow much better definition of molecular targets for functional studies. Moreover, our laboratories have strong expertise in keratinocyte biology and immunology, providing complementary platforms for the functional exploration of identified variants. Finally, it is important to note that functional analysis of individual variants is not te only goal of this research. In order to benefit patients via the development of new therapies and fulfill the promise of personalized medicine, it is of key importance to rigorously identify the molecular pathways that they delineate. Based on these considerations, we advance the hypothesis that the functions of individual genetic variants and the pathways they delineate can be identified, using currently or soon-to-be available data, given an integrated approach that integrates biostatistical and biological expertise relevant to psoriasis. To test this hypothesis, e propose the following specific aims: 1. To accurately identify causal variant candidates in psoriasis using novel statistical tools. This will be accomplished by (a) applying multiple rounds of conditional analysis and preferential linkage disequilibrium (PLD) analysis to GWAS-IChip meta-analysis, targeted resequencing, PsA GWAS, and exome array datasets; (b) expanded analysis of MHC differences between PsA and PsC; and (c) further analysis of identified variants in an expanded sample. 2. To systematically predict the potential effects of the disease-associated variants identified in Aim 1. This will be accomplished by (a) prediction of functional effects of newly-identified coding variants; (b) systematic assessment of non-coding variants utilizing the ENCODE database; (c) utilization of our RNASeq data for assessment of the effects of candidate cis-acting variants; and (d) systematic assessment of pathways likely to connect multiple variants in functional terms. 3. Functional testing of identified variants using a keratinocyte (KC)-based platform. This will be accomplished by measurement of signal transduction responses as a function of genotype for the D10N variant in TRAF3IP2 using (a) normal human keratinocytes (NHK) harvested from individuals bearing different TRAF3IP2 genotypes and (b) transfection of wild type vs variant alleles into immortalized KC with or without silencing of endogenous TRAF3IP2. We will also (c) extend this approach to predicted damaging variants identified from Aims 1 and 2 as likely to be important in KC. 4. Functional testing of identified variants using a blood-based, living-cell platform. This will be accomplished by (a) separation of monocytes and T-cells from the blood of individuals of known genotypes for the P1104A and I684S variants in TYK2, followed by measurement of signal transduction responses as a function of genotype. We will also (b) extend these studies to predicted damaging variants at other loci identified from Aims 1 and 2 as likely to be important in immunocytes.